Mosaicism, modules, and the evolution of birds: results from a Bayesian approach to the study of morphological evolution using discrete character data

Abstract

The study of morphological evolution after the inferred origin of active flight homologous with that in Aves has historically been characterized by an emphasis on anatomically disjunct, mosaic patterns of change. Relatively few prior studies have used discrete morphological character data in a phylogenetic context to quantitatively investigate morphological evolution or mosaic evolution in particular. One such previously employed method, which used summed unambiguously optimized synapomorphies, has been the basis for proposing disassociated and sequential “modernizing” or “fine-tuning” of pectoral and then pelvic locomotor systems after the origin of flight (“pectoral early-pelvic late” hypothesis). We use one of the most inclusive phylogenetic data sets of basal birds to investigate properties of this method and to consider the application of a Bayesian phylogenetic approach. Bayes factor and statistical comparisons of branch length estimates were used to evaluate support for a mosaic pattern of character change and the specific pectoral early-pelvic late hypothesis. Partitions were defined a priori based on anatomical subregion (e.g., pelvic, pectoral) and were based on those hypothesized using the summed synapomorphy approach. We compare 80 models all implementing the M(k) model for morphological data but varying in the number of anatomical subregion partitions, the models for among-partition rate variation and among-character rate variation, as well as the branch length prior. Statistical analysis reveals that partitioning data by anatomical subregion, independently estimating branch lengths for partitioned data, and use of shared or per partition gamma-shaped among-character rate distribution significantly increases estimated model likelihoods. Simulation studies reveal that partitioned models where characters are randomly assigned perform significantly worse than both the observed model and the single-partition equal-rate model, suggesting that only partitioning by anatomical subregion increases model performance. The preference for models with partitions defined a priori by anatomical subregion is consistent with a disjunctive pattern of character change for the data set investigated and may have implications for parameterization of Bayesian analyses of morphological data more generally. Statistical tests of differences in estimated branch lengths from the pectoral and pelvic partitions do not support the specific pectoral early-pelvic late hypothesis proposed from the summed synapomorphy approach; however, results suggest limited support for some pectoral branch lengths being significantly longer only early at/after the origin of flight.